NumPy
NumPy is an open source library for the Python programming language, adding support for large, multidimensional arrays, and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
- GitHub: https://github.com/topics/numpy
- Wikipedia: https://en.wikipedia.org/wiki/NumPy
- Repo: https://github.com/numpy/numpy
- Created by: Travis Oliphant
- Related Topics: python, scipy,
- Last updated: 2026-06-24 00:18:03 UTC
- JSON Representation
https://github.com/akshaypatra/expression_detector
The Expression Detector is an AI-based system that identifies and classifies human facial expressions in real-time . It utilizes computer vision and deep learning techniques to analyze facial features and determine the emotional state of a person, such as happiness, sadness, anger, surprise, fear, disgust, or neutrality.
keras-tensorflow neural-network numpy opencv-python python3
Last synced: 30 Apr 2026
https://github.com/torahappy/takasa
OpenStreetMap 高低差を考えた最短(?)経路問題ソルバー
numpy openstreetmap scipy shortest-path
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https://github.com/sralter/term_deposit_marketing
Predicting which customers will most likely purchase a type of financial product, achieving a time savings of over 93%.
matplotlib numpy optuna pandas seaborn sklearn
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https://github.com/anarya22/heart-disease-classification
Predicting heart disease using machine learning. This notebook looks into various python base ML and DS libraries in an attempt to build a machine learning model capable of predicting whether or not someone has heart disease based on their medical attributes.
data-cleaning data-visualization machine-learning matplotlib numpy pandas scikit-learn
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https://github.com/chuvalniy/torchy
Built from scratch neural network library using only NumPy
backpropogation from-scratch gradient math neural-net numpy pytorch-like
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https://github.com/athari22/house_sales_in_king_count_usa
The idea of the project is to do a Data analysis in a Real Estate Investment Trust. The Trust would like to start investing in Residential real estate.
analysis data data-science data-visualization ibm ibm-watson linearregression machine-learning matplotlib numpy pandas sklearn-library
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https://github.com/nekruzash/machine-learning-decision-trees
This is from CS2023 - AI/DS/ML class, trained a machine learning model with heart disease data sets to predict a correlation using numpy and pandas.
jupyter-notebook numpy pandas python
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https://github.com/rajharit77/weather-project
Repository for exam on the openweathermap api's project
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https://github.com/prashver/titanic-survival-prediction
This project tackles the Titanic challenge on Kaggle, predicting passenger survival based on variables like age, sex, and passenger class. The Jupyter notebook covers essential steps of a data science pipeline, including exploratory data analysis, data cleaning, feature engineering, and modeling. The dataset used is the Titanic dataset.
classification-algorithm machine-learning-algorithms matplotlib numpy pandas scikit-learn seaborn
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https://github.com/madhuresh2011/telco-customer-churn-analysis-using-python
The analysis primarily investigates factors influencing customer churn, particularly focusing on payment methods and contract types.
csv data-analysis matplotlib numpy pandas pyhton seaborn vizualisation
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Neural network library from scratch
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https://github.com/simipk12/eda-healthcare-project
Healthcare Insurance Cost Analysis This project analyzes the Healthcare Insurance dataset to explore factors that influence medical charges. The goal is to identify key drivers of insurance costs, detect outliers, and provide actionable insights for individuals, insurance companies, and policymakers.
eda matplotlib numpy pandas python seaborn
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https://github.com/priyanka7411/customer-churn-prediction
Customer Churn Prediction using machine learning. This project covers the full data science lifecycle—data cleaning, exploratory analysis, feature engineering, model building, and extracting actionable business insights.
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This repository contains personal notes, exercises, and programs from the Programming for Data Science course at Instituto Politécnico Nacional (IPN). The course focuses on using Python programming for data handling, statistical analysis, and machine learning techniques.
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This Repository consists of implementation of probability based boundary detection algorithm which gives more accurate results than canny edge detection.
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https://github.com/himel-sarder/complete-numpy
A comprehensive guide to mastering NumPy with practical examples and applications in machine learning. Perfect for learners and developers looking to deepen their knowledge of numerical computations in Python.
data-science dataanalysis machine-learning ml numpy numpy-exercises numpy-library numpy-python numpy-tutorial pythonlibrarires
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Contextual RAG Chatbot that processes PDF documents using the Google Gemini API
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https://github.com/psatler/pytorch_challenge_image_classifier
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This model was built using python and logistic regression algorithm
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https://github.com/lintangwisesa/python_recommendation_system
Basic recommendation system using Python & Sklearn
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This repository represents the End to End Machine Learning Project (Rain Fall Prediction in Australia).
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This model was built using Python and XGBoost Regression algorithm
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https://github.com/bredalis/numpy
✨ Library to work with arrays ✨
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https://github.com/duartegalvao/smart-bottle
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Bulk remove OneSignal subscribed users blazingly faster with parallel processing.
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https://github.com/yash22222/sync-intern-s-ml-tasks
SYNC INTERN'S Machine Learning internship will offer you to enhance your skills by doing real-life example projects. This internship will increase your knowledge in the field of data and algorithms to understand how a machine learns.
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Permutations, Combinations and Product for Numpy - written in Cython - 20x faster than itertools
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Multi Layer Perceptron
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In this repository, I have showcased implementation of deep learning methodologies and architectures using Python and Numpy
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Structure, build, and deploy machine learning projects
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https://github.com/mike014/soundbot
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This project focuses on classifying financial transactions using machine learning techniques. By leveraging labeled data, the model aims to categorize transactions into predefined categories (e.g., "Food," "Transport," "Shopping," etc.).
matplotlib numpy pandas-python scikitlearn-machine-learning seaborn
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Customer churn prediction is a crucial task in business analytics, helping companies identify customers who are likely to leave and take preventive actions. This project utilizes Machine Learning (ML) techniques to analyze customer behavior and predict churn.
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https://github.com/zuhairzia/customer-segmentation
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A.I, Data Science & Machine Learning and Deep Learning with Tensorflow
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https://github.com/tharushiimasha/python-practice
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api-integration csv-files file-handling json-files jupyter-notebook numpy oops-in-python pandas python web-scraping
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https://github.com/darshanpakhale250-gif/customer-churn-prediction-ml
A machine learning project to predict customer churn using regression and classification models including logistic regression, decision tree, and random forest. Performed EDA, visualizations, and model evaluation. The dataset is taken from Kaggle and implemented in Google Colab.
colab-notebook customer-churn-analysis data-science decision-trees kaggle logistic-regression machine ml numpy pandas python random-forest
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https://github.com/venkat-0706/accenture-hackathon
Developing an e-commerce recommendation system involves utilizing technologies such as Python for programming, Pandas for data manipulation, SQL for database management, FastAPI for building APIs, PostgreSQL for data storage, and Docker for containerization.
alembic api docker fastapi machinelearningalgorithms matplotlib numpy postgresql pydantic python3 scipy seaborn sqlmodel
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https://github.com/zilean12/digital-image-processing
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Last synced: 13 Apr 2026
https://github.com/harmanveer-2546/world-best-cities
Ranking of cities on social, environmental and economic factors.
best-cities-to-live-in cities continent data-loading exploratory-data-analysis geopandas hovering india matplotlib numpy os pandas plotly pre-processing seaborn visualization world world-map
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https://github.com/harmanveer-2546/prediction-of-ticket-cancellation
The objective is to develop a model that accurately predicts whether users will cancel their tickets. Each cancellation incurs a fine for the ticket registration site from the passenger company.
datetime evaluation gridsearchcv labelencoder numpy pandas standardscaler stratified-k-fold train-test-split xgboost-model
Last synced: 04 May 2026
https://github.com/ahmed-maher77/diabetes-prediction-app-using-machine-learning
Diabetes Prediction: Using machine learning to classify individuals as diabetic or non-diabetic based on health data, enabling early intervention and improved healthcare outcomes.
ai css data-science gradientboostinclassifier javascript logisticregression machine-learning matplotlib numpy pandas python randomforestclassifier seaborn streamlit supportvectormachine webdevelopment
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Crop Recommendation System is a powerful tool for enhancing agricultural decision-making. By leveraging data-driven insights, it empowers farmers to maximize yield and ensure sustainable practices.
adaboostclassifier bagging-classifier csv decision-trees gaussian html knn-classification logistic-regression machine-learning machine-learning-algorithms matplotlib model numpy pandas random-forest random-forest-classifier scikit-learn seaborn svc
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https://github.com/zuhairzia/titanic-survival-project
This is a Titanic Survival Prediction Model developed using Python, Pandas, Scikit-learn, and Jupyter Notebook. The model predicts whether a passenger survived the Titanic disaster based on features such as age, gender, and passenger class.
csv-dataset flask jupyter-notebook matplotlib numpy pandas pandas-library python scikit-learn seaborn streamlit
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https://github.com/unvercan/activation-function-comparison-pytorch
Comparison of common activation functions on MNIST dataset using PyTorch.
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https://github.com/nandinimarepalli/ai_ml_internship_projects
Projects completed during my AI/ML and Data Expert internship, including EDA, machine learning models, and dashboard development using Python, pandas, scikit-learn, and visualization libraries.
matplotlib numpy pandas python scikit-learn seaborn
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Global Content Strategy: Leveraging Data Insights to Optimize Netflix's International Growth
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An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.
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A fraude de cartão de crédito é uma forma comum de fraude que afeta milhões de pessoas em todo o mundo. Essa fraude pode ter consequências graves, tanto para as vítimas quanto para as instituições financeiras que emitem os cartões de crédito.
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Tasks for the SCIT Work Shop.
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High-Level Wrappers for Building and Manipulating Numpy Arrays
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https://github.com/rkarahul/face-detection-using-opencv-
•Build a face detection project using OpenCV and haar cascades, which are the better choice for real-time detection.
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https://github.com/pardhuu66/college-id-validator
FastAPI-based offline College ID Validator with Docker support
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https://github.com/msikorski93/Linear-Regression-From-Scratch
Different solutions of linear and polynomial regression made from scratch.
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https://github.com/yipjunkai/pyvolr
Modern Black-Scholes-Merton pricing, Greeks, and implied volatility for Python. Rust core. Drop-in replacement for the abandoned py_vollib.
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A comprehensive collection of Python programming resources, from basics to advanced concepts. Built for learners, by learners
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Predictive Analysis & Early Detection of Brain stroke using Machine Learning Algorithm
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https://github.com/towaquimbayo/comp-4948
BCIT Computer Systems Technology (CST) - COMP 4948 (Predictive Machine Learning)
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https://github.com/waghraj1699/fraud-detection-project
A fraud detection system with machine learning will be able to detect risk based on your historical data
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https://github.com/harmanveer-2546/finding-you-next-perfect-house
In this exploratory data analysis, we compare a dataset which consists of various features about renting of houses available on these renting platforms listed by owners of these houses, and try to derive some constructive conclusions by performing Descriptive statistics of the available features.
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Phase 1 of Data Science project (program) to perform Exploratory Data Analysis on Terrorism using Python On Google Colab for Coderscave Internship sept 2023
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2D vortex particle method (Gaussian-core) with RK4, viscosity, plots, animations
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